REVIEW article
Front. Artif. Intell.
Sec. Medicine and Public Health
Volume 8 - 2025 | doi: 10.3389/frai.2025.1608778
Can Artificial Intelligence Improve the Diagnosis and Prognosis of Disorders of Consciousness? A Scoping Review
Provisionally accepted
Mirjam Bonanno1
Davide Cardile1*
Piergiuseppe Liuzzi2
Antonio Celesti3Giuseppe Micali1
Francesco Corallo1Angelo Quartarone1Francesco Tomaiuolo4Rocco Salvatore Calabrò1- 1Bonino Pulejo Neurology Center (IRCCS), Messina, Italy
- 2IRCCS Don Carlo Gnocchi Firenze, Florence, Tuscany, Italy
- 3Department of Mathematics and Computer Science, Physics and Earth Sciences, University of Messina, Messina, Italy
- 4Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
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Background. Artificial intelligence (AI), in the form of machine learning (ML) or deep learning (DL) models, can aid clinicians in the diagnostic process and/or in the prognosis of critically medical conditions, as for patients with a disorder of consciousness (DoC), in which both aspects are particularly challenging. DoC is a category of neurological impairments that are mainly caused by severe acquired brain injury, like ischemic or hemorrhagic strokes or traumatic injuries. The aim of this scoping review is to map the literature on the role of ML and DL in the field of diagnosis and prognosis of DoCs. Materials and Methods. A scoping search, started from 3rd October 2024, was conducted for all peer-reviewed articles published from 2000 to 2024, using the following databases: PubMed, Embase, Scopus and Cochrane Library.
Keywords: artificial intelligence, machine learning, deep learning, interpretability; diagnosis, prognosis, Neurorehabilitation, disorder of consciousness
Received: 09 Apr 2025; Accepted: 09 May 2025.
Copyright: © 2025 Bonanno, Cardile, Liuzzi, Celesti, Micali, Corallo, Quartarone, Tomaiuolo and Calabrò. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Davide Cardile, Bonino Pulejo Neurology Center (IRCCS), Messina, Italy
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.